Co-citation Clustering
Updated 2026-08-10
INTRODUCTION
English translation pending.
CORE DEFINITION
A bibliometric technique that builds a network from co-citation links and applies clustering algorithms to it. The core proposition is that documents repeatedly cited together by the same later works occupy a shared position in the knowledge structure, so clusters of such documents correspond to research themes. The key qualification is that co-citation strength measures perceived association and is sensitive to the time window chosen.
SCAFFOLDING EFFECT
Reduce cognitive load
- Network construction: build the citation matrix and compute co-citation frequencies. - Similarity normalization: standardize similarity so large fields do not dominate the clustering. - Cluster reading: interpret each cluster as a theme and track how clusters merge or split.
Anchor fast decisions
When a group of later papers repeatedly cites the same earlier works, those earlier works are functioning as a shared foundation for that line of research. Aggregating the pattern across the literature turns it into a weighted graph, and clustering that graph separates the field into coherent thematic communities. Changes in the graph over time show themes emerging, converging, or dissolving.
MINIMUM ACTION
In progress 0/1Practice this model in one real situation:
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Source support: Explicit
- en.wikipedia.orghttps://en.wikipedia.org/wiki/Co-citationverified
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